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192 records · Page 11

Driving rapid atomic order in MnAl via low-magnitude magnetic field annealing

Application of a mild (60 mT), uniform magnetic field during short-term thermal treatment of kinetically retained, atomically disordered (paramagnetic) ε-MnAl was found to deliver a significant ~50 % increase in the formation of L1 0 atomically ordered (ferromagnetic) τ-MnAl product phase, compared to that produced by conventional (i.e., zero-field) annealing under identical thermal conditions. The magnetic field, applied in a passive closed-circuit configuration during annealing, induced significant changes in the structural, magnetic, and phase evolution of the material. Computational results based on electronic structure calculations demonstrate that the effective magnetic susceptibility of τ-MnAl is sensitive to the orientation, rather than the magnitude, of an applied magnetic field in the vicinity of the Curie temperature. The uniaxial magnetocrystalline anisotropy of the L1 0 structure is proposed to act as a filter for selective propagation of the population of τ-MnAl variants that are favorably aligned with the applied field. In this manner, crystallographic “gridlock” is alleviated that would otherwise arise from the coexistence of multiple, energetically equivalent τ-phase variants within the parent ε-phase matrix. These results confirm that static, low-magnitude magnetic field annealing is able to accelerate L1 0 atomic ordering in the MnAl system and likely can exert similar influences in relevant magnetic systems, facilitating efficient tailoring of structure-sensitive magnetic properties for the manufacture of magnetic materials.

36 MATERIALS SCIENCE↗

Smart Pixels: In-pixel AI for on-sensor data filtering

We present a smart pixel prototype readout integrated circuit (ROIC) designed in CMOS 28 nm bulk process, with in-pixel implementation of an artificial intelligence (AI) / machine learning (ML) based data filtering algorithm designed as proof-of-principle for a Phase III upgrade at the Large Hadron Collider (LHC) pixel detector. The first version of the ROIC consists of two matrices of 256 smart pixels, each 25$\times$25 µm\textsuperscript{2} in size. Each pixel consists of a charge-sensitive preamplifier with leakage current compensation and three auto-zero comparators for a 2-bit flash-type ADC. The frontend is capable of synchronously digitizing the sensor charge within 25 ns. Measurement results show an equivalent noise charge (ENC) of $\sim$30e\textsuperscript{-} and a total dispersion of $\sim$100e\textsuperscript{-} The second version of the ROIC uses a fully connected two-layer neural network (NN) to process information from a cluster of 256 pixels to determine if the pattern corresponds to highly desirable high-momentum particle tracks for selection and readout. The digital NN is embedded in-between analog signal processing regions of the 256 pixels without increasing the pixel size and is implemented as fully combinatorial digital logic to minimize power consumption and eliminate clock distribution, and is active only in the presence of an input signal. The total power consumption of the neural network is $\sim$ 300 $\mu$W. The NN performs momentum classification based on the generated cluster patterns and even with a modest momentum threshold, it is capable of 54.4\% – 75.4\% total data rejection, opening the possibility of using the pixel information at 40MHz for the trigger. The total power consumption of analog and digital functions per pixel is $\sim$ 6 $\mu$W per pixel, which corresponds to $\sim$ 1 W/cm\textsuperscript{2} staying within the experimental constraints.

Parpillon, Benjamin↗

Smart Pixels: In-pixel AI for on-sensor data filtering

We present a smart pixel prototype readout integrated circuit (ROIC) designed in CMOS 28 nm bulk process, with in-pixel implementation of an artificial intelligence (AI) / machine learning (ML) based data filtering algorithm designed as proof-of-principle for a Phase III upgrade at the Large Hadron Collider (LHC) pixel detector. The first version of the ROIC consists of two matrices of 256 smart pixels, each 25$\times$25 $\mu$m$^2$ in size. Each pixel consists of a charge-sensitive preamplifier with leakage current compensation and three auto-zero comparators for a 2-bit flash-type ADC. The frontend is capable of synchronously digitizing the sensor charge within 25 ns. Measurement results show an equivalent noise charge (ENC) of $\sim$30e$^-$ and a total dispersion of $\sim$100e$^-$ The second version of the ROIC uses a fully connected two-layer neural network (NN) to process information from a cluster of 256 pixels to determine if the pattern corresponds to highly desirable high-momentum particle tracks for selection and readout. The digital NN is embedded in-between analog signal processing regions of the 256 pixels without increasing the pixel size and is implemented as fully combinatorial digital logic to minimize power consumption and eliminate clock distribution, and is active only in the presence of an input signal. The total power consumption of the neural network is $\sim$ 300 $\mu$W. The NN performs momentum classification based on the generated cluster patterns and even with a modest momentum threshold, it is capable of 54.4% - 75.4% total data rejection, opening the possibility of using the pixel information at 40MHz for the trigger. The total power consumption of analog and digital functions per pixel is $\sim$ 6 $\mu$W per pixel, which corresponds to $\sim$ 1 W/cm$^2$ staying within the experimental constraints.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗

Strain-engineered high-responsivity MoTe 2 photodetector for silicon photonic integrated circuits

In integrated photonics, specific wavelengths are preferred such as 1550 nm due to low-loss transmission and the availability of optical gain in this spectral region. For chip-based photodetectors, layered two-dimensional (2D) materials bear scientific and technologically relevant properties such as electrostatic tunability and strong light-matter interactions. However, no efficient photodetector in the telecommunication C-band has been realized with 2D transition metal dichalcogenide materials due to their large optical bandgap. Furthermore, we demonstrate a MoTe 2 -based photodetector featuring strong photoresponse (responsivity = 0.5 A/W -1 ) operating at 1550 nm in silicon photonics enabled by strain engineering the 2D material. Non-planarized waveguide structures show a locally-induced bandgap change of 0.2 eV inside MoTe 2 , resulting in large photo-response, in an otherwise photo-inactive medium when unstrained. Unlike Graphene-based photodetectors relying on a gapless band structure, this photodetector shows a ~100X improved dark current, enabling an efficient noise equivalent power of 90 pW/Hz -0.5 . Such strain-engineered integrated photodetector provides new opportunities for integrated optoelectronic systems.

47 OTHER INSTRUMENTATION↗

Nonlocal, diamagnetic electromagnetic effects in magnetically insulated transmission lines

We identify the time-dependent physics responsible for the critical reduction of current losses in magnetically insulated transmission lines (MITLs) due to uninsulated space charge-limited currents of electrons emitted by field stress. A drive current of sufficiently short pulse length introduces a strong enough time dependence that steady-state results alone become inadequate for the complete understanding of current losses. The time-dependent physics can be described as a nonlocal, diamagnetic electromagnetic response of space charge limited currents. As the pulse length is increased or equivalently, the MITL length reduced, these time-dependent effects diminish and current losses converge to those predicted by the well-known Child–Langmuir law in the external (vacuum) fields. We present a simple one-dimensional (1D) model that encapsulates the essence of this physics. We find excellent agreement with 2D particle-in-cell simulations for two MITL geometries, Cartesian parallel plate and azimuthally symmetric straight coaxial. Based on the 1D model, we explore various scaling dependencies of MITL losses with relevant parameters, e.g., peak current, pulse length, geometrical dimensions, etc. We propose an improved physics model of magnetic insulation in the form of a Hull curve, which could also help improve predictions of current losses by common circuit element codes, such as BERTHA. Finally, we describe how to calculate the temperature rise due to electron impact within the 1D model.

Computer simulation↗

Simulating Effective QED on Quantum Computers

In recent years simulations of chemistry and condensed materials has emerged as one of the preeminent applications of quantum computing, offering an exponential speedup for the solution of the electronic structure for certain strongly correlated electronic systems. To date, most treatments have ignored the question of whether relativistic effects, which are described most generally by quantum electrodynamics (QED), can also be simulated on a quantum computer in polynomial time. Here we show that effective QED, which is equivalent to QED to second order in perturbation theory, can be simulated in polynomial time under reasonable assumptions while properly treating all four components of the wavefunction of the fermionic field. In particular, we provide a detailed analysis of such simulations in position and momentum basis using Trotter-Suzuki formulas. We find that the number of T -gates needed to perform such simulations on a 3 D lattice of n s sites scales at worst as O ( n s 3 / ϵ ) 1 + o ( 1 ) in the thermodynamic limit for position basis simulations and O ( n s 4 + 2 / 3 / ϵ ) 1 + o ( 1 ) in momentum basis. We also find that qubitization scales slightly better with a worst case scaling of O ~ ( n s 2 + 2 / 3 / ϵ ) for lattice eQED and complications in the prepare circuit leads to a slightly worse scaling in momentum basis of O ~ ( n s 5 + 2 / 3 / ϵ ) . We further provide concrete gate counts for simulating a relativistic version of the uniform electron gas that show challenging problems can be simulated using fewer than 10 13 non-Clifford operations and also provide a detailed discussion of how to prepare multi-reference configuration interaction states in effective QED which can provide a reasonable initial guess for the ground state. Finally, we estimate the planewave cutoffs needed to accurately simulate heavy elements such as gold.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗

Improving wafer-scale Josephson junction resistance variation in superconducting quantum coherent circuits

Quantum bits, or qubits, are an example of coherent circuits envisioned for next-generation computers and detectors. A robust superconducting qubit with a coherent lifetime of O (100 µs) is the transmon: a Josephson junction functioning as a non-linear inductor shunted with a capacitor to form an anharmonic oscillator. In a complex device with many such transmons, precise control over each qubit frequency is often required, and thus variations of the junction area and tunnel barrier thickness must be sufficiently minimized to achieve optimal performance while avoiding spectral overlap between neighboring circuits. Simply transplanting our recipe optimized for single, stand-alone devices to wafer-scale (producing 64, 1x1 cm dies from a 150 mm wafer) initially resulted in global drifts in room-temperature tunneling resistance of ± 30%. Inferring a critical current variation from this resistance distribution, we present an optimized process developed from a systematic 38 wafer study that results in < 3.5% relative standard deviation (RSD) in critical current ( ) for 3000 Josephson junctions (both single-junctions and asymmetric SQUIDs) across an area of 49 cm 2 . Looking within a 1x1 cm moving window across the substrate gives an estimate of the variation characteristic of a given qubit chip. Our best process, utilizing ultrasonically assisted development, uniform ashing, and dynamic oxidation has shown = 1.8% within 1x1 cm, on average, with a few 1x1 cm areas having < 1.0% (equivalent to < 0.5%). Such stability would drastically improve the yield of multi-junction chips with strict critical current requirements.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗

A Sub-electron-noise Skipper-CCD Readout ASIC with Improved Channel-to-channel Isolation and an Integrated Cryogenic Voltage Reference

The MIDNA application specific integrated circuits (ASICs) are a series of skipper-CCD readout chips fabricated in a 65 nm low-power CMOS process that implement a correlated double sampling signal processing chain based on dual-slope integrators. They are capable of working from room to cryogenic temperatures, down to 84 K. The present iteration of the ASIC has been fabricated including several design updates and the addition of an on-chip voltage reference, resulting in improved performance. This work presents the main vulnerabilities solved, the changes carried out, and the resulting performance benefits. Measurements with a skipper-CCD and the ASIC at 140 K showed that the single-electron resolution can be reached by averaging the measured charge in the analog domain using the analog pile-up technique with a readout noise as low as 0.11 erms of equivalent charge for 1200 samples. The channel-to-channel crosstalk was also characterized showing values better than -62 dB.

Alcalde Bessia, Fabricio↗

A Sub-electron-noise Skipper-CCD Readout ASIC with Improved Channel-to-channel Isolation and an Integrated Cryogenic Voltage Reference

The MIDNA application specific integrated circuits (ASICs) are a series of skipper-CCD readout chips fabricated in a 65 nm low-power CMOS process that implement a correlated double sampling signal processing chain based on dual-slope integrators. They are capable of working from room to cryogenic temperatures, down to 84 K. The present iteration of the ASIC has been fabricated including several design updates and the addition of an on-chip voltage reference, resulting in improved performance. This work presents the main vulnerabilities solved, the changes carried out, and the resulting performance benefits. Measurements with a skipper-CCD and the ASIC at 140 K showed that the single-electron resolution can be reached by averaging the measured charge in the analog domain using the analog pile-up technique with a readout noise as low as 0.11 erms of equivalent charge for 1200 samples. The channel-to-channel crosstalk was also characterized showing values better than -62 dB.

Alcalde Bessia, Fabricio↗

A phenomenological rate of injection model for predicting fuel injection with application to mixture formation in light-duty diesel engines

Fuel injection rate laws are one of the most important pieces of information needed when modeling engine combustion with computational fluid dynamics. In this study, a simple phenomenological model of a common-rail injector was developed and calibrated for the Bosch CRI2.2 platform. The model requires three tunable parameter fits, making it relatively easy to calibrate and suitable for injector modeling when high-fidelity information about the internal injector’s geometry and electrical circuit details are not available. Each injection pulse is modeled as a sequence of up to four stages: an injection needle mechanical opening transient, a full-lift viscous flow inertial transient, a Bernoulli steady-state stage, and a needle descent transient. Parameters for each stage are obtained as polynomial fits from measured injection rate properties. The model enforces total injected mass, and the intermediate stages are only introduced if the injection pulse duration is long enough. Experimental rates of injection from two separate campaigns on the same injector were used to calibrate the model. The model was first validated against measured injection rate laws featuring pilot injections, short partially premixed combustion pulses, and conventional diesel combustion injection strategies. Then, it was employed as an input to engine computational fluid dynamics simulations, which were run to simulate experiments of mixture formation in an optically accessible light-duty diesel engine. It was found that, though simple, this model is capable of predicting both pilot and main injection pulse mass flow rates well: the simulations yielded accurate predictions of in-cylinder equivalence ratio distributions from injection strategies for both partially premixed combustion and pilot injections. Also, once calibrated, the model produced appropriate results for a wide range of injected mass and rail pressure values. Finally, it was observed that usage of such a relatively simple model can be a good choice when high-fidelity injection rate input and highly detailed information of the injector’s geometry and operation are not available, particularly as noticeable discrepancies can be present also among different experimental campaigns on similar hardware.

42 ENGINEERING↗

Differential Ligation Alters Electronic State and Coupling Signals of Iron-Sulfur Clusters in Flavin-Based Electron Bifurcation

Flavin-based electron bifurcation (FBEB) is employed by microorganisms for controlling pools of redox equivalents by reversibly splitting electron pairs into high- and low-energy levels from an initial midpoint potential. Our ability to harness this phenomenon is crucial for biocatalytic design which is limited by our understanding of energy coupling in the bifurcation system. In Pyrococcus furiosus, FBEB is carried out by the NADH-dependent ferredoxin:NADP+-oxidoreductase (NfnSL), coupling the uphill reduction of ferredoxin in NfnL to the downhill reduction of NAD+ in NfnS from oxidation of NADPH. Flanking the bifurcating flavin are two site-differentiated iron-sulfur clusters; the nearest is a glutamate-ligated [4Fe-4S] cluster in NfnL. Recent biochemical experiments substituting the native glutamate with cysteine led to loss of coupling between the uphill and downhill pathways, in contrast to the tight thermodynamic coupling in the native system. To understand how this decoupling is biochemically manifested by the cysteine-substituted [4Fe-4S] in NfnL, we employed electron paramagnetic resonance (EPR) spectroscopy to identify changes in electronic architecture and square wave voltammetry (SWV) to probe thermodynamic shifts produced by the substitution. We observed notable g-value shifts in the EPR for the cysteine-substituted iron-sulfur cluster in addition to significant downward shifts in the redox potential, as well as the disappearance of several low-field signals observed in the native NfnSL complex. These results suggest the site-differentiated glutamate residue facilitates higher spin states in the [4Fesingle bond4S] cluster to bridge energetic gaps in electron transfer to the bifurcating flavin in the native complex, preventing unwanted short-circuiting seen in the cysteine-substituted complex.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

NMDQi Thermal-hydraulic Optimization, Analysis, and Scoping Tool (TOAST)

The Thermal-hydraulic Optimization, Analysis, and Scoping Tool (TOAST) is developed to support the thermal-hydraulic aspects for the design of optimal irradiation vehicles for the Nuclear Materials Discovery and Qualification initiative (NMDQi). TOAST is currently a MATLAB-based tool that utilizes a simplified steady-state analytical model where a radial thermal resistance circuit is utilized to account for conduction through up to 2 capsules, a gas gap, a thermal bond, a sample cladding, and a sample, as well as the convection from a water coolant outside the capsules. The geometry is discretized axially along the user-defined height of a basket with a user-defined number of points/nodes, essentially turning TOAST into a semi-2D heat transfer analysis utility for cylindrical irradiation vehicles with practically any configuration, solving for temperatures radially at multiple axial locations. TOAST utilizes a Graphical User Interface (GUI) in-which a user can define the geometrical layout, the materials utilized for each component, the coolant characteristics, and the required solution. The user can define the geometry by inputting the diameters, thicknesses, and heights for each component, whereas the materials are defined via the user-provided constant or variable thermal conductivities. The user can select the coolant's inlet temperature, pressure, and the pressure drop across the height of the problem (which is used to calculate the velocity of the flow). Finally, the user can choose to solve for a sample heat generation rate limit by inputting temperature limits for the sample and capsules or can choose to purely solve for the axial temperature distributions of each component by inputting a pre-selected heat generation rate. Either way, TOAST provides the user with axial temperature distributions of all the components including the coolant, and the heat generation rate limit as well as the maximum outlet coolant temperature. The user can also choose to do one of 6 sensitivity analyses in TOAST. The sensitivity analyses yield plots of the sensitivity of the heat generation rate limit, the maximum coolant temperature, and the pressure limit for the annular components due to perturbations in 1-2 unknown variables based on the selected sensitivity analysis. Benchmarks between computations in TOAST and equivalent 2D axis symmetric ABAQUS models are presented, showing that TOAST results are within less than 3% of ABAQUS results in most cases, and a maximum of 8% difference in some cases. The benchmarks also revealed that this uncertainty is tied to the selection of an appropriate Nusselt number correlation and appropriate thermal conductivities, which the user can do from the GUI. Regardless, TOAST is demonstrated as a computationally efficient, highly accessible, and accurate utility for optimization and scoping s of studies different irradiation vehicles.

42 ENGINEERING↗